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UMKC Announces New Master of Science in Artificial Intelligence
Ai Infrastructure

UMKC Announces New Master of Science in Artificial Intelligence

UMKC announces a new Master of Science in Artificial Intelligence program aimed at addressing workforce demand for AI expertise, set to l...

AI News - General · 4 min ·
Machine Learning

[D] ICML 2026 Average Score

Hi all, I’m curious about the current review dynamics for ICML 2026, especially after the rebuttal phase. For those who are reviewers (or...

Reddit - Machine Learning · 1 min ·
Accelerating science with AI and simulations
Machine Learning

Accelerating science with AI and simulations

MIT Professor Rafael Gómez-Bombarelli discusses the transformative potential of AI in scientific research, emphasizing its role in materi...

AI News - General · 10 min ·

All Content

[2602.20520] How Do Inpainting Artifacts Propagate to Language?
Llms

[2602.20520] How Do Inpainting Artifacts Propagate to Language?

This paper investigates how visual artifacts from diffusion-based inpainting affect language generation in vision-language models, reveal...

arXiv - AI · 3 min ·
[2602.20492] Wireless Federated Multi-Task LLM Fine-Tuning via Sparse-and-Orthogonal LoRA
Llms

[2602.20492] Wireless Federated Multi-Task LLM Fine-Tuning via Sparse-and-Orthogonal LoRA

This paper presents a novel approach to decentralized federated learning for multi-task large language model fine-tuning, addressing key ...

arXiv - Machine Learning · 4 min ·
[2602.20467] Elimination-compensation pruning for fully-connected neural networks
Machine Learning

[2602.20467] Elimination-compensation pruning for fully-connected neural networks

This paper introduces a novel pruning method for fully-connected neural networks, which compensates for the removal of weights by adjusti...

arXiv - Machine Learning · 4 min ·
[2602.20449] Protein Language Models Diverge from Natural Language: Comparative Analysis and Improved Inference
Llms

[2602.20449] Protein Language Models Diverge from Natural Language: Comparative Analysis and Improved Inference

This article explores the differences between protein language models (PLMs) and natural language models, highlighting how these distinct...

arXiv - Machine Learning · 4 min ·
[2602.20442] Imputation of Unknown Missingness in Sparse Electronic Health Records
Machine Learning

[2602.20442] Imputation of Unknown Missingness in Sparse Electronic Health Records

The paper presents a novel algorithm for imputing unknown missing values in sparse electronic health records (EHRs) using a transformer-b...

arXiv - Machine Learning · 4 min ·
[2602.20344] Hierarchical Molecular Representation Learning via Fragment-Based Self-Supervised Embedding Prediction
Nlp

[2602.20344] Hierarchical Molecular Representation Learning via Fragment-Based Self-Supervised Embedding Prediction

This article presents GraSPNet, a novel hierarchical self-supervised learning framework for molecular representation that enhances graph ...

arXiv - Machine Learning · 3 min ·
[2602.20317] Fast Spectrogram Event Extraction via Offline Self-Supervised Learning: From Fusion Diagnostics to Bioacoustics
Machine Learning

[2602.20317] Fast Spectrogram Event Extraction via Offline Self-Supervised Learning: From Fusion Diagnostics to Bioacoustics

This article presents a self-supervised learning framework for the automated extraction of coherent and transient modes from high-noise t...

arXiv - AI · 3 min ·
[2602.20306] Shape-informed cardiac mechanics surrogates in data-scarce regimes via geometric encoding and generative augmentation
Machine Learning

[2602.20306] Shape-informed cardiac mechanics surrogates in data-scarce regimes via geometric encoding and generative augmentation

This article presents a novel framework for creating shape-informed surrogates in cardiac mechanics, enhancing predictions in data-scarce...

arXiv - Machine Learning · 4 min ·
[2602.20224] Exploring Anti-Aging Literature via ConvexTopics and Large Language Models
Llms

[2602.20224] Exploring Anti-Aging Literature via ConvexTopics and Large Language Models

This article presents a novel clustering algorithm for analyzing anti-aging literature, improving topic modeling through convex optimizat...

arXiv - Machine Learning · 3 min ·
[2602.20271] Uncertainty-Aware Delivery Delay Duration Prediction via Multi-Task Deep Learning
Machine Learning

[2602.20271] Uncertainty-Aware Delivery Delay Duration Prediction via Multi-Task Deep Learning

This paper presents a multi-task deep learning model for predicting delivery delay durations in logistics, addressing challenges posed by...

arXiv - Machine Learning · 4 min ·
[2602.20223] MultiModalPFN: Extending Prior-Data Fitted Networks for Multimodal Tabular Learning
Llms

[2602.20223] MultiModalPFN: Extending Prior-Data Fitted Networks for Multimodal Tabular Learning

The paper introduces MultiModalPFN, an extension of TabPFN designed for multimodal tabular learning, effectively integrating diverse data...

arXiv - Machine Learning · 3 min ·
[2602.20210] Multimodal Crystal Flow: Any-to-Any Modality Generation for Unified Crystal Modeling
Machine Learning

[2602.20210] Multimodal Crystal Flow: Any-to-Any Modality Generation for Unified Crystal Modeling

The paper presents Multimodal Crystal Flow (MCFlow), a unified model for crystal generation tasks that enhances performance by integratin...

arXiv - Machine Learning · 3 min ·
[2602.20208] Model Merging in the Essential Subspace
Machine Learning

[2602.20208] Model Merging in the Essential Subspace

This paper presents ESM, a novel framework for merging multiple task-specific models into a single multi-task model, addressing inter-tas...

arXiv - Machine Learning · 3 min ·
[2602.20204] Analyzing Latency Hiding and Parallelism in an MLIR-based AI Kernel Compiler
Machine Learning

[2602.20204] Analyzing Latency Hiding and Parallelism in an MLIR-based AI Kernel Compiler

This paper analyzes the effectiveness of latency hiding and parallelism techniques in an MLIR-based AI kernel compiler, focusing on vecto...

arXiv - AI · 3 min ·
[2602.20202] Evaluating the Reliability of Digital Forensic Evidence Discovered by Large Language Model: A Case Study
Llms

[2602.20202] Evaluating the Reliability of Digital Forensic Evidence Discovered by Large Language Model: A Case Study

This paper evaluates the reliability of digital forensic evidence identified by large language models (LLMs), proposing a structured fram...

arXiv - AI · 4 min ·
[2602.20199] IMOVNO+: A Regional Partitioning and Meta-Heuristic Ensemble Framework for Imbalanced Multi-Class Learning
Machine Learning

[2602.20199] IMOVNO+: A Regional Partitioning and Meta-Heuristic Ensemble Framework for Imbalanced Multi-Class Learning

The paper introduces IMOVNO+, a framework designed to enhance data quality and algorithmic robustness in imbalanced multi-class learning ...

arXiv - Machine Learning · 4 min ·
[2602.20187] AINet: Anchor Instances Learning for Regional Heterogeneity in Whole Slide Image
Machine Learning

[2602.20187] AINet: Anchor Instances Learning for Regional Heterogeneity in Whole Slide Image

The paper introduces AINet, a novel framework for whole slide image analysis that addresses regional heterogeneity through anchor instanc...

arXiv - AI · 4 min ·
[2602.20177] Enhancing Heat Sink Efficiency in MOSFETs using Physics Informed Neural Networks: A Systematic Study on Coolant Velocity Estimation
Machine Learning

[2602.20177] Enhancing Heat Sink Efficiency in MOSFETs using Physics Informed Neural Networks: A Systematic Study on Coolant Velocity Estimation

This study explores the use of Physics Informed Neural Networks (PINNs) to optimize coolant velocity for enhancing heat sink efficiency i...

arXiv - Machine Learning · 4 min ·
[2602.20168] Benchmarking Early Deterioration Prediction Across Hospital-Rich and MCI-Like Emergency Triage Under Constrained Sensing
Machine Learning

[2602.20168] Benchmarking Early Deterioration Prediction Across Hospital-Rich and MCI-Like Emergency Triage Under Constrained Sensing

This article presents a benchmarking framework for early deterioration prediction in emergency triage, comparing hospital-rich settings w...

arXiv - Machine Learning · 3 min ·
[2602.20166] ConceptRM: The Quest to Mitigate Alert Fatigue through Consensus-Based Purity-Driven Data Cleaning for Reflection Modelling
Machine Learning

[2602.20166] ConceptRM: The Quest to Mitigate Alert Fatigue through Consensus-Based Purity-Driven Data Cleaning for Reflection Modelling

The paper presents ConceptRM, a novel method aimed at reducing alert fatigue in intelligent agents by improving data cleaning processes f...

arXiv - AI · 4 min ·
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Machine Learning Large Language Models Generative AI Natural Language Processing Computer Vision Robotics & Embodied AI

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